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	- Pykhtin Local Exposure Volatility Shell (10, 11)
	- Pykhtin Local Exposure Volatility Trajectory (12)
	- Pykhtin Local Exposure Volatility Constructor (13, 14, 15)
	- Portfolio MPoR Exposure Generator Shell (41)
	- Portfolio MPoR Exposure Generator Components (42)
	- Portfolio MPoR Variation Margin Estimate (43, 44)
	- Portfolio MPoR Trade Payments Estimate (45, 46)
	- Variation Margin Trade Payment Vertex (47)
	- Numeraire MPoR Dense Trade Payments (48, 49)
	- Fixed Dense Trade Payments #1 (50, 51)
	- Fixed Dense Trade Payments #2 (52, 53)
	- Float Stream Dense Trade Payments (54, 55)
	- Fixed Float Dense Trade Payments (56, 57)
	- Porfolio Dense Trade Payments Array (58, 59)
	- Exposue Holdings Position Group Estimator (60)


Bug Fixes/Clean-up:

Samples:

	- Exposure Path Brownian Bridge #1 (1, 2)
	- Brownian Bridge Dense Exposure Average (3, 4)
	- Brownian Bridge Dense Exposure Minimum (5)
	- Brownian Bridge Dense Exposure Maximum (6)
	- Brownian Bridge Dense Exposure Error (7, 8, 9)
	- Exposure Path Brownian Bridge #2 (16, 17, 18)
	- Exposure Path Fix Float Shell (19)
	- Exposure Path Fix Float State Generator (20)
	- Exposure Path Fix Float #1 (21, 22)
	- Exposure Path Fix Float #2 (23, 24)
	- Exposure Path Fix Float #3 (25, 26)
	- Exposure Path Fix Float #4 (27, 28)
	- Exposure Path Fix Float #5 (29, 30)
	- Exposure Path Fix Float #6 (31, 32)
	- Exposure Path Fix Float #7 (33, 34)
	- Exposure Path Fix Float #8 (35, 36)
	- Exposure Path Fix Float #9 (37, 38)
	- Exposure Path Fix Float #10 (39, 40)
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lakshmiDRIP committed Jun 16, 2018
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2 changes: 1 addition & 1 deletion AssetAllocationLibrary.html
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<section>
<p align="center"><img src="https://github.com/lakshmiDRIP/DROP/blob/master/DRIP_Logo.gif?raw=true" width="100"></p>

<p><strong>v3.52</strong> <em>2 Jun 2018</em></p>
<p><strong>v3.54</strong> <em>15 Jun 2018</em></p>

<p>DROP Asset Allocation Library is a component of the <a href="https://lakshmidrip.github.io/DROP/AssetAllocationModule.html">DROP Asset Allocation Module</a>. It is composed of:</p>

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<section>
<p align="center"><img src="https://github.com/lakshmiDRIP/DROP/blob/master/DRIP_Logo.gif?raw=true" width="100"></p>

<p><strong>v3.52</strong> <em>2 Jun 2018</em></p>
<p><strong>v3.54</strong> <em>15 Jun 2018</em></p>

<p>DROP Asset Allocation Module is a collection of model libraries for MPT framework, Black Litterman Strategy Incorporator, Holdings Constraint, and Transaction Costs.</p>

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<section>
<p align="center"><img src="https://github.com/lakshmiDRIP/DROP/blob/master/DRIP_Logo.gif?raw=true" width="100"></p>

<p><strong>v3.52</strong> <em>2 Jun 2018</em></p>
<p><strong>v3.54</strong> <em>15 Jun 2018</em></p>

<p>DROP Asset Backed Analytics Library is a component of the <a href="https://lakshmidrip.github.io/DROP/FixedIncomeModule.html">DROP Fixed Income Module</a>. It is composed of:</p>

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<section>
<p align="center"><img src="https://github.com/lakshmiDRIP/DROP/blob/master/DRIP_Logo.gif?raw=true" width="100"></p>

<p><strong>v3.52</strong> <em>2 Jun 2018</em></p>
<p><strong>v3.54</strong> <em>15 Jun 2018</em></p>

<p>DROP Fixed Income Analytics Library is a component of the <a href="https://lakshmidrip.github.io/DROP/FixedIncomeModule.html">DROP Fixed Income Module</a>. It is composed of:</p>

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Expand Up @@ -29,7 +29,7 @@ <h1>DROP</h1>
<section>
<p align="center"><img src="https://github.com/lakshmiDRIP/DROP/blob/master/DRIP_Logo.gif?raw=true" width="100"></p>

<p><strong>v3.52</strong> <em>2 Jun 2018</em></p>
<p><strong>v3.54</strong> <em>15 Jun 2018</em></p>

<p>DROP Fixed Income is a collection of Java libraries for Instrument/Trading Conventions, Treasury Futures/Options, Funding/Forward/Overnight Curves, Multi-Curve Construction/Valuation, Collateral Valuation and XVA Metric Generation, Calibration and Hedge Attributions, Statistical Curve Construction, Bond RV Metrics, Stochastic Evolution and Option Pricing, Interest Rate Dynamics and Option Pricing, LMM Extensions/Calibrations/Greeks, Algorithmic Differentiation, and Asset Backed Models and Analytics.</p>

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